On the Resilience of an Ant-based System in Fuzzy Environments. An Empirical Study
This addresses optimization robustness for problems with uncertain data, but is incremental as it applies an existing method to fuzzy variants.
The study investigated how the MAX-MIN Ant System optimization method performs in fuzzy environments using Traveling Salesman Problem instances, finding that it shows good resilience and adaptability to data uncertainty.
The current work describes an empirical study conducted in order to investigate the behavior of an optimization method in a fuzzy environment. MAX-MIN Ant System, an efficient implementation of a heuristic method is used for solving an optimization problem derived from the Traveling Salesman Problem (TSP). Several publicly-available symmetric TSP instances and their fuzzy variants are tested in order to extract some general features. The entry data was adapted by introducing a two-dimensional systematic degree of fuzziness, proportional with the number of nodes, the dimension of the instance and also with the distances between nodes, the scale of the instance. The results show that our proposed method can handle the data uncertainty, showing good resilience and adaptability.